The credit card industry is changing rapidly. As the number of outstanding credit cards and the associated risk increase, banks, credit unions, financial institutions and other credit card issuers must increase their focus on the collections process or risk falling behind their competitors.
Non-payment of credit card debt, credit card defaults and bankruptcies have cost the retail consumer credit industry billions of dollars in revenue. Thus, there is a need to determine the most cost effective and efficient collection strategies to be used on delinquent accounts. Furthermore, there is a need to automate and, thereby improve the determination as to what specific collection strategy should be used on a particular delinquent account or how collection resources should be divided among all delinquent accounts.
With delinquent accounts another area of concern is how to minimize "negative rolling" a circumstance in which an account rolls over into a higher delinquency level. Such accounts need to be identified automatically in advance to prevent such negative rolling. Very few efforts have been made to understand, or attempt to predict, the outcome of a contact with a consumer or credit card member by use of computerized record keeping. Heretofore, a consumer was contacted again and again with varying degrees of intensity. A phone contact could result in a payment made on the account or alienation of the consumer. Since consumer alienation is generally to be avoided, an automated predictive process or technique that minimizes consumer alienation is an important collection tool. Moreover, some consumers respond better to mailings than phone contacts or respond to second contacts but not first contacts. Insight into the likely response of a consumer achieved through computerized analysis greatly improve the likelihood of a successful contact.
Equally importantly, for a credit card issuer, and its collection department or collection agency, is to determine from its computer database how to optimize the use of collection resources. For example, use of collection resource `A`, a phone contact agent for example, may result in a certain aggregate payment amount from two separate accounts. However, use of collection resource `A` against one of the accounts and a cheaper collection resource `B`, a mailing for example, against the other account might result in the same aggregate total income, but at a lower cost.
One attempt to address the problem of optimizing resource allocation is an article entitled "Managing Consumer Credit Delinquency in the US Economy: A Multi-Billion Dollar Management Science Application" by William M. Makuch et al., Interfaces, vol. 22, January-February 1992, pages 90-109. The Makuch article describes a system for managing credit card delinquency debt by improving the allocation of limited collection resources to maximize net collection over multiple billing periods. Unlike the present system, the calculation of the Makuch system is performed with the assignment of a constant collection strategy used for all billing periods. One of the overall goal of the present system is to automatically determine the optimal collection strategy to utilize in order to select the most efficient collection method for each account for each billing cycle.